• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.21 no.2
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• pp.63-71
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• 2010

Objectives : The aim of this study was to investigate the effect of the clinical and demographic variables such as body weight, dosage, family history of attention-deficit hyperactivity disorder (ADHD), and psychiatric co-morbidity on the side-effects of OROS-Methylphenidate (OROS-MPH), and to evaluate the relationship between drug response and side effect severity. Methods : A total of 144 children (ages 6-18) with diagnosed ADHD were treated with OROS-MPH. Children were examined at baseline and after 1, 3, 6, 9, and 12 weeks of each treatment condition. The stimulant drug side effect rating scale (SERS), pulse rate, systolic blood pressure, diastolic blood pressure, and electrocardiogram (ECG) were evaluated to assess side effect profiles. Changes in these parameters from baseline were examined and analyzed. Results : Anorexia (30.95%) and insomnia (13.10%) were the most commonly reported side effects during this study. Insomnia and loss of appetite score increased at one week follow-up, but was sustained or decreased as treatment progressed. Small but significant increases in pulse rate and diastolic blood pressure were observed during treatment ; however, no clinically meaningful changes in ECG parameters were noted during the study. Low body weight, high dosage of OROS-MPH, and family history of ADHD were associated with cardiovascular side effect. In contrast, there was no significant relationship between OROS-MPH treatment response and the severity of side effect and no difference resulted between the responder and non-responder groups with respect to OROS-MPH dosage in the 12 weeks of follow-up. Conclusion : To the best of our knowledge, this study is the first Korean study to investigate comprehensive side effect profiles and their correlates in OROS-MPH treatment for ADHD children. OROS-MPH was well tolerated with no clinically significant side effects during the treatment period. In conclusion, low body weight, high dosage of OROSMPH, and family history of ADHD could be used as predictive factors in increasing pulse rate and blood pressure.

• Korean Journal of Ecology and Environment
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• v.35 no.3 s.99
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• pp.160-171
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• 2002

The impact of summer monsoon on water quality of the lower Nakdong River was evaluated during the summer (June-August) in 1997. Several limnological variables were measured in the interval of $1{\sim}3$ day using an automatic monitoring system (Hydrolab $Recorder^{TM}$) to detect water quality changes caused by rainfall on onehour basis. During the monsoon period (from late June to mid July), 5 times of major rainfall events of >50 mm were recorded in the river basin. Dynamic changes of water quality were observed during the monsoon, and the first rainfall event (June$25{\sim}27$) had a significant influence on the water quality at the lower part of the river. All Parameters were largely changed due to the first rain event, and the changed level was maintained until the end of monsoon period. Nutrient concentrations and turbidity increased and values of the other parameters were declined as a result of water dilution. This rainfall event, Changma, is a meteorological phenomenon caused by the East-Asian monsoon climate. The magnitude and frequency of the rainfall during the early monsoon play an important role in change of water quality and ecosystem characteristics of large river systems.

• Korean Journal of Ecology and Environment
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• v.42 no.1
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• pp.1-8
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• 2009

This study used a mesocosm which presumes movement of the nutrient (especially $PO_{4^-}P$) in the wetland. After setting up the mesocosm inside the wetland and adding the $PO_{4^-}P$, observed the movement of the $PO_{4^-}P$ every hour. We analyzed the variables which had the possibility of affecting $PO_{4^-}P$ concentration in the wetland-flora, absorbing rate of algae, settling rate, release rate. Immediately after adding $PO_{4^-}P$, the concentration of the TP in water column at each mesocosm was 0.48, 12.4, 20.4, $23.6\;mg\;L^{-1}$, after 21 days they were 0.6, 1.92, 6.97 and $6.94\;mg\;L^{-1}$ respectively. The concentration of the TP in water column at the mesocosm decreased on average 73.7%. The concentration of the $PO_{4^-}P$ inside reed, algae and sediment in the mesocosm was increased from $0.73mg\;gDW^{-1}$, $3.81mg\;gDW^{-1}$, $466.1mg\;kg^{-1}$ to $0.83mg\;gDW^{-1}$, $4.57mg\;gDW^{-1}$ and $813.3mg\;kg^{-1}$ respectively. Algae is more sensitive than reeds in absorption of the nutrient. TP removal by settling was highest. Budgeting of TP indicated that P moved from particulates in the water column to sediment and algae. Immediately after adding $PO_{4^-}P$, water column (24.2%) and sediment (49.0%) dominated TP storage, with algae (10.3%) and reed (16.4%) holding smaller proportions of TP. After 21 days, Sediment (59.0%) and algae (17.9%) dominated TP storage, with water column (7.1%) and reed (15.8%) holding smaller proportions of TP. Estimation of phosphate movement using mesocosms is an appropriate method because wetlands have many controlling factors. Analysed data can be compared to background data for wetland construction and management.

• Journal of Nutrition and Health
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• v.47 no.2
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• pp.124-133
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• 2014

Purpose: The current study was designed for development of a simplified malnutrition screening tool (SMST) for hospitalized patients using readily available laboratory and patient information and for evaluation of its reliability compared to well-established tools, such as PGSGA and NRS-2002. Methods: Anthropometric and biochemical measurements, as well as a few subjective assessments, of 903 patients who were preclassified by their nutritional status according to PGSGA were analyzed. Among them, a combination of factors, including age, BMI, albumin, cholesterol, total protein, hematocrit, and changes in body weight and food intake, were statistically selected as variables for SMST. Results: According to SMST, 620 patients (68.7%) were classified as the normal group and 283 patients (31.3%) were classified as the malnutrition group. Significant differences in age, albumin, TLC, BMI, hemoglobin, hematocrit, total protein, cholesterol, and length of stay were observed between the two groups. For inter-methods reliability, the screening results by SMST were compared with those by PGSGA and NRS-2002. The comparison with PGSGA and NRS-2002 showed 'Substantial agreement' (sensitivity 94.4%, specificity 88.4%, ${\kappa}$ = 0.747) and 'Moderate agreement' (sensitivity 96.1%, specificity 79.5%, ${\kappa}$ = 0.505), respectively, indicating that SMST held high inter-methods reliability. Conclusion: In conclusion, SMST, based on readily available laboratory and patient information and simple subjective assessments on changes in food intake and body weight, may be a useful alternative tool with a simple but reliable risk index, especially in resource-limited domestic hospitals.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.245-256
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• 2021

This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.

• Korean Journal of Breeding Science
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• v.42 no.1
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• pp.40-49
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• 2010

This study was conducted to examine genetic variation on leaf characteristics of Zelkova serrata populations. Leaf samples were obtained from eighteen populations and fourteen leaf characteristics such as leaf blade length, leaf width, leaf area and etc. were measured. In all leaf characteristics, there were significant differences among populations and among individuals within population. Most variance of leaf characteristics was contributed to among individuals within population except for length from leaf base to maximum width (x3) and the ratio of x3 to leaf blade length (x10). The relatively high variations of leaf characteristics were found at Gurye, Jungeup and Gyungju populations while Youngwol, Cheongsong, Youngchun populations showed the lower variation. There was high correlation among leaf characteristics related to leaf size, but not among the variables of ratio between leaf characteristics. Length from leaf base to maximum width(x3) and the ratio of x3 to x10 showed significant positive correlation with latitude and altitude of populations, which reflect the differences of mean annual temperature among populations. Mean annual rainfall of populations showed negative correlation with leaf blade length, leaf width, length from apex to first serration and leaf area. Four principal components (PC) were deduced from principal component analysis, which explain the 88.5% of total variance of leaf characteristics. Leaf area, length from leaf base to maximum width, serration number and petiole length showed the highest contribution to PC1, PC2, PC3, PC4, respectively. According to cluster analysis, the populations of Z. serrata were divided into two groups, which reflect the difference of mean annual temperature between groups. Within group, however, specific tendency of clustering was not observed among populattions.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.85-96
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• 2019

Solar radiation is an important variable for estimation of energy balance and water cycle in natural and agricultural ecosystems. A deep neural network (DNN) model has been developed in order to estimate the daily global solar radiation. Temperature and precipitation, which would have wider availability from weather stations than other variables such as sunshine duration, were used as inputs to the DNN model. Five-fold cross-validation was applied to train and test the DNN models. Meteorological data at 15 weather stations were collected for a long term period, e.g., > 30 years in Korea. The DNN model obtained from the cross-validation had relatively small value of RMSE ($3.75MJ\;m^{-2}\;d^{-1}$) for estimates of the daily solar radiation at the weather station in Suwon. The DNN model explained about 68% of variation in observed solar radiation at the Suwon weather station. It was found that the measurements of solar radiation in 1985 and 1998 were considerably low for a small period of time compared with sunshine duration. This suggested that assessment of the quality for the observation data for solar radiation would be needed in further studies. When data for those years were excluded from the data analysis, the DNN model had slightly greater degree of agreement statistics. For example, the values of $R^2$ and RMSE were 0.72 and $3.55MJ\;m^{-2}\;d^{-1}$, respectively. Our results indicate that a DNN would be useful for the development a solar radiation estimation model using temperature and precipitation, which are usually available for downscaled scenario data for future climate conditions. Thus, such a DNN model would be useful for the impact assessment of climate change on crop production where solar radiation is used as a required input variable to a crop model.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.51-60
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• 2019

The major purpose of this study is to construct an in-situ soil moisture verification network employing Frequency Domain Reflectometry (FDR) sensors for Cosmic-ray soil moisture observation system operation as well as long-term field-scale soil moisture monitoring. The test bed of Cosmic-ray and FDR verification network system was established at the Sulma Catchment, in connection with the existing instrumentations for integrated data provision of various hydrologic variables. This test bed includes one Cosmic-ray Neutron Probe (CRNP) and ten FDR stations with four different measurement depths (10 cm, 20 cm, 30 cm, and 40 cm) at each station, and has been operating since July 2018. Furthermore, to assess the reliability of the in-situ verification network, the volumetric water content data measured by FDR sensors were compared to those calculated through the core sampling method. The evaluation results of FDR sensors- measured soil moisture against sampling method during the study period indicated a reasonable agreement, with average values of $bias=-0.03m^3/m^3$ and RMSE $0.03m^3/m^3$, revealing that this FDR network is adequate to provide long-term reliable field-scale soil moisture monitoring at Sulmacheon basin. In addition, soil moisture time series observed at all FDR stations during the study period generally respond well to the rainfall events; and at some locations, the characteristics of rainfall water intercepted by canopy were also identified. The Temporal Stability Analysis (TSA) was performed for all FDR stations located within the CRNP footprint at each measurement depth to determine the representative locations for field-average soil moisture at different soil profiles of the verification network. The TSA results showed that superior performances were obtained at FDR 5 for 10 cm depth, FDR 8 for 20 cm depth, FDR2 for 30 cm depth, and FDR1 for 40 cm depth, respectively; demonstrating that those aforementioned stations can be regarded as temporal stable locations to represent field mean soil moisture measurements at their corresponding measurement depths. Although the limit on study duration has been presented, the analysis results of this study can provide useful knowledge on soil moisture variability and stability at the test bed, as well as supporting the utilization of the Cosmic-ray observation system for long-term field-scale soil moisture monitoring.